Scaling a multilingual vision-language model in size and training breadth yields new state-of-the-art results on over 25 benchmarks plus emerging abilities in counting and multilingual detection.
Open-domain visual entity recognition: Towards recognizing millions of wikipedia entities
2 Pith papers cite this work. Polarity classification is still indexing.
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The EReL@MIR 2025 Track 1 challenge evaluates single systems on two multimodal retrieval tasks and finds that Qwen2-VL decoder-based embedders dominate, with a training-free entry within 0.1 points of the fine-tuned winner.
citing papers explorer
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PaLI-X: On Scaling up a Multilingual Vision and Language Model
Scaling a multilingual vision-language model in size and training breadth yields new state-of-the-art results on over 25 benchmarks plus emerging abilities in counting and multilingual detection.
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Overview of the EReL@MIR 2025 Multimodal Document Retrieval Challenge (Track 1)
The EReL@MIR 2025 Track 1 challenge evaluates single systems on two multimodal retrieval tasks and finds that Qwen2-VL decoder-based embedders dominate, with a training-free entry within 0.1 points of the fine-tuned winner.